Google Vision Api
•Download as PPTX, PDF•
1 like•2,002 views
Cloud Vision API allows users to upload images to detect labels, faces, and logos through an integrated REST API. It can detect multiple faces in an image and identify associated attributes, but does not support facial recognition. Users can request different annotation types per image by uploading to the API or integrating with Google Cloud Storage. For any questions, users can email the contact provided.
Report
Share
Report
Share
Recommended
Google Cloud Vision API
Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API. It quickly classifies images into thousands of categories (e.g., "sailboat", "lion", "Eiffel Tower"), detects individual objects and faces within images, and finds and reads printed words contained within images. You can build metadata on your image catalog, moderate offensive content, or enable new marketing scenarios through image sentiment analysis. Analyze images uploaded in the request or integrate with your image storage on Google Cloud Storage.
Ad Tech 개요
NBT의 Ad Tech 교육자료 입니다.
아래의 링크에서 교육영상도 보실 수 있습니다.
https://www.youtube.com/watch?v=jr4QwCQ9I50&list=PLdWpPj-RibJsrc5NzIsO9TKs3ac4HBg8Z
게임엔진과 공간정보 3D 콘텐츠 융합 : Cesium for Unreal
강력한 시각화와 몰입도 높은 가상세계 표현을 위해, 게임엔진은 측량기반의 콘텐츠를 필요로 하고 공간정보 3D 플랫폼은 강력한 프리미엄급 클라이언트를 필요로 하는데, Cesium for Unreal은 이런 수요를 만족하는 솔루션입니다. 이 발표자료는 공간정보 3D 콘텐츠가 어떻게 게임엔진 안으로 들어가서 국가 또는 지구 범위로 확장성을 발휘하는지, 그 기능구현을 진입단계 수준으로 소개하고 있습니다.
Liferay as a Microservice Platform
This document discusses Liferay as a microservice platform. It begins by describing some issues with monolithic applications, such as high complexity, limited scalability and reusability. It then introduces microservices as an approach to break applications into independently deployable services. While microservices reduce complexity within each component, they can increase operational overhead and introduce new challenges around network communication and coordination. The document argues that Liferay's use of OSGi addresses many microservice goals while avoiding some of the operational overhead, and that its modular architecture provides a natural path for applications to evolve from monoliths to microservices over time.
공간정보 최근 동향과 디지털트윈, 메타버스
2023년 3월 28일 수자원공사 인력개발원에서 특강한 자료입니다. 공간정보 분야의 최근 동향, 공간정보 관점에서 디지털트윈, 메타버스 등에 관해 정리해 봤습니다.
안정적인 서비스 운영 2014.03
2013년 NHN Entertainment 신입사원 교육을 위해서 시작한 강의로 현재는 사내 경력직 대상으로도 진행하는 교육입니다.
교육을 진행하면서 바뀐 내용은 계속 업데이트하고 있습니다.
피드백 환영합니다!
Recommended
Google Cloud Vision API
Google Cloud Vision API enables developers to understand the content of an image by encapsulating powerful machine learning models in an easy to use REST API. It quickly classifies images into thousands of categories (e.g., "sailboat", "lion", "Eiffel Tower"), detects individual objects and faces within images, and finds and reads printed words contained within images. You can build metadata on your image catalog, moderate offensive content, or enable new marketing scenarios through image sentiment analysis. Analyze images uploaded in the request or integrate with your image storage on Google Cloud Storage.
Ad Tech 개요
NBT의 Ad Tech 교육자료 입니다.
아래의 링크에서 교육영상도 보실 수 있습니다.
https://www.youtube.com/watch?v=jr4QwCQ9I50&list=PLdWpPj-RibJsrc5NzIsO9TKs3ac4HBg8Z
게임엔진과 공간정보 3D 콘텐츠 융합 : Cesium for Unreal
강력한 시각화와 몰입도 높은 가상세계 표현을 위해, 게임엔진은 측량기반의 콘텐츠를 필요로 하고 공간정보 3D 플랫폼은 강력한 프리미엄급 클라이언트를 필요로 하는데, Cesium for Unreal은 이런 수요를 만족하는 솔루션입니다. 이 발표자료는 공간정보 3D 콘텐츠가 어떻게 게임엔진 안으로 들어가서 국가 또는 지구 범위로 확장성을 발휘하는지, 그 기능구현을 진입단계 수준으로 소개하고 있습니다.
Liferay as a Microservice Platform
This document discusses Liferay as a microservice platform. It begins by describing some issues with monolithic applications, such as high complexity, limited scalability and reusability. It then introduces microservices as an approach to break applications into independently deployable services. While microservices reduce complexity within each component, they can increase operational overhead and introduce new challenges around network communication and coordination. The document argues that Liferay's use of OSGi addresses many microservice goals while avoiding some of the operational overhead, and that its modular architecture provides a natural path for applications to evolve from monoliths to microservices over time.
공간정보 최근 동향과 디지털트윈, 메타버스
2023년 3월 28일 수자원공사 인력개발원에서 특강한 자료입니다. 공간정보 분야의 최근 동향, 공간정보 관점에서 디지털트윈, 메타버스 등에 관해 정리해 봤습니다.
안정적인 서비스 운영 2014.03
2013년 NHN Entertainment 신입사원 교육을 위해서 시작한 강의로 현재는 사내 경력직 대상으로도 진행하는 교육입니다.
교육을 진행하면서 바뀐 내용은 계속 업데이트하고 있습니다.
피드백 환영합니다!
Discover BigQuery ML, build your own CREATE MODEL statement
With BigQuery ML, you can build machine learning models without leaving the database environment and training it on massive datasets. In this demo session we are going to demonstrate common marketing Machine Learning use cases of how to build, train, eval, and predict, your own scalable machine learning models using SQL language in Google BigQuery and to address the following use cases: - Customer Segmentation + Product cross sale recommendation - Conversion/Purchase prediction - Inference with other in-built >20 models The audience will get first-hand experience with how to write CREATE MODEL sql syntax to build machine learning models such as: - Multiclass logistic regression for classification - K-means clustering - Matrix factorization - ARIMA time series predictions ... and more Models are trained and accessed in BigQuery using SQL — a language data analysts know. This enables business decision-making through predictive analytics across the organization without leaving the query editor. In the end, the audience will learn how everyday developers can build/train/run their own machine-learning models straight from the database query editor, by issuing CREATE MODEL statements
From Monolith to Microservices
This document provides an overview of microservices architecture and how to implement it using Amazon ECS and Docker containers. It discusses what microservices are, characteristics of the architecture, and how ECS provides a fully managed platform for deploying and scheduling containers. It also covers task placement strategies, running services on ECS, and reference architectures like continuous deployment, secrets management, and service discovery that align with the twelve-factor app methodology. Finally, it introduces Blox, an open source project that aims to simplify deploying and managing microservices on ECS.
The Best of Both Worlds: Introducing WSO2 API Manager 4.0.0
APIs now serve as the primary building blocks for assembling data, events, and services from within the organization, throughout ecosystems, and across devices. Integrated legacy systems and support for modern event-driven architectures, on the other hand, are critical in allowing timely, relevant digital experiences in response to customer behavior. To support these demands, WSO2 has added significant new capabilities to WSO2 API Manager 4.0.0.
Complete support for streaming APIs and event-driven architecture (EDA)
The first solution to support full implementation of the AsyncAPI specification
A Service Catalog to enable developers to discover a given service seamlessly
API / API product revisioning to keep track of the changes
Feature-rich, cloud-based analytics for easy integration
You will gain a full understanding of WSO2 API Manager 4.0.0 features and how they cater to current API Management demands by attending this webinar.
DURING THE WEBINAR, WE WILL COVER:
Experience the power and synergy of Service Integration and API Management in a fully functional API ecosystem
Understand the motivation behind WSO2 API Manager 4.0.0 release
New streaming and event-driven architecture support available in API Manager 4.0.0
Learn the importance of catering all API Management and integration demands with one connected platform
Explore other new features and enhancements to the product
Intro to Github Actions @likecoin
Github Action is the CI/CD tool made by Github. Deeply integrated with Github features, it can not only automate deployments, but also Githu.b repository management. In this sharing I will talk about how we use Github action in LikeCoin and some issues we encountered.
Computer vision
This document provides an overview of computer vision techniques including:
1. Using pre-trained CNN models for tasks like classification and object detection. Popular models discussed include AlexNet, VGG, ResNet, YOLO, and DenseNet.
2. Basic CNN operations like convolution, pooling, dropout, and normalization. Feature extraction using CNNs and techniques like transfer learning and fine-tuning pretrained models.
3. Additional computer vision tasks covered include object detection using Haar cascades, stereo vision, pattern detection, and reconstructing images from CNN features. Frameworks like PyTorch and libraries like TensorFlow are also mentioned.
Yolov5
The document describes the architecture of 4 YOLOv5 object detection models of different sizes - small, medium, large, and extra large. Each model uses the same basic building blocks of focus, convolutional, and bottleneck CSP layers followed by upsampling and concatenation, but with different input channel sizes and numbers of layers to process images of different resolutions.
Deep Learning for Computer Vision: Data Augmentation (UPC 2016)
http://imatge-upc.github.io/telecombcn-2016-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of big annotated data and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which had been addressed until now with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or text captioning.
[DLHacks 実装]Perceptual Adversarial Networks for Image-to-Image Transformation
The document discusses two papers on image-to-image translation: Pix2Pix and PAN. Pix2Pix uses a conditional GAN with adversarial and per-pixel losses. PAN builds on Pix2Pix by adding a perceptual adversarial loss using the discriminator's features. This additional loss helps the discriminator better detect differences between real and fake images. The document provides examples of tasks like deraining and inpainting that both frameworks can address and compares their results. It concludes by discussing the author's implementation of Pix2Pix and PAN and results showing Pix2Pix generally outperforming PAN, potentially due to issues like the need for per-pixel loss or patch discriminator design.
Perceptrons (D1L2 2017 UPC Deep Learning for Computer Vision)
https://telecombcn-dl.github.io/2017-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
Fisheye/Omnidirectional View in Autonomous Driving IV
FisheyeMultiNet: Real-time Multi-task Learning Architecture for
Surround-view Automated Parking System
• Generalized Object Detection on Fisheye Cameras for Autonomous
Driving: Dataset, Representations and Baseline
• SynWoodScape: Synthetic Surround-view Fisheye Camera Dataset for
Autonomous Driving
• Feasible Self-Calibration of Larger Field-of-View (FOV) Camera Sensors
for the ADAS
image classification
The document discusses image classification using deep learning techniques. It introduces image classification and its goal to assign labels to images based on their content. It then discusses using the Anaconda platform and TensorFlow library for building neural networks to perform image classification in Python. Convolutional neural networks are proposed as an effective method, involving steps like convolution, pooling and fully connected layers to classify images. A demonstration of the technique and future applications like computer vision are also mentioned.
Real-time CG animation in Unity: unpacking the Sherman project - Unite Copenh...
This document summarizes the animated short film "Sherman" which was created entirely with Unity. It discusses how the film was blocked out and animated without storyboards. Advanced animation techniques like Alembic were used. Custom fur and visual effects were also implemented. Lighting was achieved through light probes, reflection probes, and baked global illumination. The project structure and Unity's capabilities for film production are discussed, as well as future directions like modular projects and Addressables.
Observability For You and Me with OpenTelemetry
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Video Classification Basic
This presentation covers the following topics-
1. Video Classification as a sequence of frames
2. Video Classification as a sequence of frame-blocks
3. 2D ConvNets for Videos
4. CNN + LSTM
라이브드론맵 (Live Drone Map) - 실시간 드론 매핑 솔루션
This document introduces Live Drone Map, a UAV-based rapid mapping and sharing solution. It consists of a UAV system that can automatically acquire geospatial data through sensors and process the data in real-time to generate orthoimages. The orthoimages are then uploaded and visualized in a cloud-based geospatial platform called Mago3D. This allows users to access and view mapping data updated in real-time from UAV flights through a web browser or mobile devices. The system is proposed to provide updated mapping for UN field operations by automating data acquisition, processing and sharing.
Google Cloud vision
First time back at my alma mater after graduation to speak about Google's newly introduced Cloud Vision API and some awesome use cases for it in student projects and why they should be excited about it.
Android Studio & Cloud Vision API 玩圖像辨識
機器人和無人駕駛越來越接近我我們的生活，圖像辨識也相對越應用於程式開發，Google 已經提供一個好用的API，就來探索圖像辨識的魔力吧
More Related Content
What's hot
Discover BigQuery ML, build your own CREATE MODEL statement
With BigQuery ML, you can build machine learning models without leaving the database environment and training it on massive datasets. In this demo session we are going to demonstrate common marketing Machine Learning use cases of how to build, train, eval, and predict, your own scalable machine learning models using SQL language in Google BigQuery and to address the following use cases: - Customer Segmentation + Product cross sale recommendation - Conversion/Purchase prediction - Inference with other in-built >20 models The audience will get first-hand experience with how to write CREATE MODEL sql syntax to build machine learning models such as: - Multiclass logistic regression for classification - K-means clustering - Matrix factorization - ARIMA time series predictions ... and more Models are trained and accessed in BigQuery using SQL — a language data analysts know. This enables business decision-making through predictive analytics across the organization without leaving the query editor. In the end, the audience will learn how everyday developers can build/train/run their own machine-learning models straight from the database query editor, by issuing CREATE MODEL statements
From Monolith to Microservices
This document provides an overview of microservices architecture and how to implement it using Amazon ECS and Docker containers. It discusses what microservices are, characteristics of the architecture, and how ECS provides a fully managed platform for deploying and scheduling containers. It also covers task placement strategies, running services on ECS, and reference architectures like continuous deployment, secrets management, and service discovery that align with the twelve-factor app methodology. Finally, it introduces Blox, an open source project that aims to simplify deploying and managing microservices on ECS.
The Best of Both Worlds: Introducing WSO2 API Manager 4.0.0
APIs now serve as the primary building blocks for assembling data, events, and services from within the organization, throughout ecosystems, and across devices. Integrated legacy systems and support for modern event-driven architectures, on the other hand, are critical in allowing timely, relevant digital experiences in response to customer behavior. To support these demands, WSO2 has added significant new capabilities to WSO2 API Manager 4.0.0.
Complete support for streaming APIs and event-driven architecture (EDA)
The first solution to support full implementation of the AsyncAPI specification
A Service Catalog to enable developers to discover a given service seamlessly
API / API product revisioning to keep track of the changes
Feature-rich, cloud-based analytics for easy integration
You will gain a full understanding of WSO2 API Manager 4.0.0 features and how they cater to current API Management demands by attending this webinar.
DURING THE WEBINAR, WE WILL COVER:
Experience the power and synergy of Service Integration and API Management in a fully functional API ecosystem
Understand the motivation behind WSO2 API Manager 4.0.0 release
New streaming and event-driven architecture support available in API Manager 4.0.0
Learn the importance of catering all API Management and integration demands with one connected platform
Explore other new features and enhancements to the product
Intro to Github Actions @likecoin
Github Action is the CI/CD tool made by Github. Deeply integrated with Github features, it can not only automate deployments, but also Githu.b repository management. In this sharing I will talk about how we use Github action in LikeCoin and some issues we encountered.
Computer vision
This document provides an overview of computer vision techniques including:
1. Using pre-trained CNN models for tasks like classification and object detection. Popular models discussed include AlexNet, VGG, ResNet, YOLO, and DenseNet.
2. Basic CNN operations like convolution, pooling, dropout, and normalization. Feature extraction using CNNs and techniques like transfer learning and fine-tuning pretrained models.
3. Additional computer vision tasks covered include object detection using Haar cascades, stereo vision, pattern detection, and reconstructing images from CNN features. Frameworks like PyTorch and libraries like TensorFlow are also mentioned.
Yolov5
The document describes the architecture of 4 YOLOv5 object detection models of different sizes - small, medium, large, and extra large. Each model uses the same basic building blocks of focus, convolutional, and bottleneck CSP layers followed by upsampling and concatenation, but with different input channel sizes and numbers of layers to process images of different resolutions.
Deep Learning for Computer Vision: Data Augmentation (UPC 2016)
http://imatge-upc.github.io/telecombcn-2016-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of big annotated data and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which had been addressed until now with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or text captioning.
[DLHacks 実装]Perceptual Adversarial Networks for Image-to-Image Transformation
The document discusses two papers on image-to-image translation: Pix2Pix and PAN. Pix2Pix uses a conditional GAN with adversarial and per-pixel losses. PAN builds on Pix2Pix by adding a perceptual adversarial loss using the discriminator's features. This additional loss helps the discriminator better detect differences between real and fake images. The document provides examples of tasks like deraining and inpainting that both frameworks can address and compares their results. It concludes by discussing the author's implementation of Pix2Pix and PAN and results showing Pix2Pix generally outperforming PAN, potentially due to issues like the need for per-pixel loss or patch discriminator design.
Perceptrons (D1L2 2017 UPC Deep Learning for Computer Vision)
https://telecombcn-dl.github.io/2017-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
Fisheye/Omnidirectional View in Autonomous Driving IV
FisheyeMultiNet: Real-time Multi-task Learning Architecture for
Surround-view Automated Parking System
• Generalized Object Detection on Fisheye Cameras for Autonomous
Driving: Dataset, Representations and Baseline
• SynWoodScape: Synthetic Surround-view Fisheye Camera Dataset for
Autonomous Driving
• Feasible Self-Calibration of Larger Field-of-View (FOV) Camera Sensors
for the ADAS
image classification
The document discusses image classification using deep learning techniques. It introduces image classification and its goal to assign labels to images based on their content. It then discusses using the Anaconda platform and TensorFlow library for building neural networks to perform image classification in Python. Convolutional neural networks are proposed as an effective method, involving steps like convolution, pooling and fully connected layers to classify images. A demonstration of the technique and future applications like computer vision are also mentioned.
Real-time CG animation in Unity: unpacking the Sherman project - Unite Copenh...
This document summarizes the animated short film "Sherman" which was created entirely with Unity. It discusses how the film was blocked out and animated without storyboards. Advanced animation techniques like Alembic were used. Custom fur and visual effects were also implemented. Lighting was achieved through light probes, reflection probes, and baked global illumination. The project structure and Unity's capabilities for film production are discussed, as well as future directions like modular projects and Addressables.
Observability For You and Me with OpenTelemetry
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Video Classification Basic
This presentation covers the following topics-
1. Video Classification as a sequence of frames
2. Video Classification as a sequence of frame-blocks
3. 2D ConvNets for Videos
4. CNN + LSTM
라이브드론맵 (Live Drone Map) - 실시간 드론 매핑 솔루션
This document introduces Live Drone Map, a UAV-based rapid mapping and sharing solution. It consists of a UAV system that can automatically acquire geospatial data through sensors and process the data in real-time to generate orthoimages. The orthoimages are then uploaded and visualized in a cloud-based geospatial platform called Mago3D. This allows users to access and view mapping data updated in real-time from UAV flights through a web browser or mobile devices. The system is proposed to provide updated mapping for UN field operations by automating data acquisition, processing and sharing.
What's hot (20)
Discover BigQuery ML, build your own CREATE MODEL statement
Discover BigQuery ML, build your own CREATE MODEL statement
The Best of Both Worlds: Introducing WSO2 API Manager 4.0.0
The Best of Both Worlds: Introducing WSO2 API Manager 4.0.0
Deep Learning for Computer Vision: Data Augmentation (UPC 2016)
Deep Learning for Computer Vision: Data Augmentation (UPC 2016)
[DLHacks 実装]Perceptual Adversarial Networks for Image-to-Image Transformation
[DLHacks 実装]Perceptual Adversarial Networks for Image-to-Image Transformation
Perceptrons (D1L2 2017 UPC Deep Learning for Computer Vision)
Perceptrons (D1L2 2017 UPC Deep Learning for Computer Vision)
Fisheye/Omnidirectional View in Autonomous Driving IV
Fisheye/Omnidirectional View in Autonomous Driving IV
Real-time CG animation in Unity: unpacking the Sherman project - Unite Copenh...
Real-time CG animation in Unity: unpacking the Sherman project - Unite Copenh...
Viewers also liked
Google Cloud vision
First time back at my alma mater after graduation to speak about Google's newly introduced Cloud Vision API and some awesome use cases for it in student projects and why they should be excited about it.
Android Studio & Cloud Vision API 玩圖像辨識
機器人和無人駕駛越來越接近我我們的生活，圖像辨識也相對越應用於程式開發，Google 已經提供一個好用的API，就來探索圖像辨識的魔力吧
Neural networks and google tensor flow
Slides for the Neural Network and Google TensorFlow presentation at the Grand Rapids Google I/O extended event.
Machine learning with Google machine learning APIs - Puppy or Muffin?
Machine learning with Google machine learning APIs - Puppy or Muffin?Bret McGowen - NYC Google Developer Advocate
The document provides an overview of machine learning APIs available through Google Cloud Platform including Vision API, Speech API, and Natural Language API. It discusses how each API can be used to perform tasks like image labeling and detection, speech transcription, sentiment analysis, and entity recognition. Examples of API requests and responses are also provided. The document is intended to demonstrate how machine learning APIs can be easily leveraged to build applications.Google Cloud Platform Empowers TensorFlow and Machine Learning
Google Cloud Platform empowers TensorFlow and machine learning by providing scalable computing resources and APIs. It allows developers to build neural networks with TensorFlow, and easily integrate pre-trained machine learning models into applications using Cloud Vision and Speech APIs. Cloud Machine Learning offers a managed service for distributed TensorFlow training and prediction at scale in the cloud.
3.1 sqtm qms
This document outlines three upcoming lectures on quality systems: Quality Management Systems (QMS) for software, Statistical Process Control (SPC), and Software Process Improvement (CMM). The first lecture will cover the historical perspectives of QMS from Deming, Juran, and Crosby; the elements and procedures of a QMS; and the four principal aspects of a QMS for software: development procedures, quality control, quality improvement, and quality assurance. It will also introduce the concept of Statistical Process Control.
Google Machine Learning APIs - puppies or muffins?
Want to take advantage of machine learning without building and training your own models? The Google Cloud Vision and Speech APIs expose the machine learning functionality behind Google Photos, Google Images, and the speech recognition in “Ok, Google.” Developers can now build these features into their apps with a simple REST API call.
This deck gives an overview of Google Cloud Vision API, Cloud Speech API, and the Cloud Natural Language API.
Big Data Ready Enterprise
The document describes Big Data Ready Enterprise (BDRE), an open source product that addresses common challenges in implementing and operating big data solutions at large scale. It provides out-of-the-box features to accelerate implementations using pluggable architecture, community support, and distribution compatibility. The document outlines BDRE's key benefits and capabilities for data ingestion, workflow automation, operational metadata management, and more. It also provides examples of BDRE implementations and screenshots of the product's interface.
Machine Learning for Any Size of Data, Any Type of Data
The document discusses Google Cloud Platform machine learning capabilities for unstructured data like text, speech and images. It introduces the Cloud Vision, Speech and Translate APIs which provide pre-trained machine learning models through REST interfaces to understand unstructured data without requiring ML expertise. Examples are given of using the APIs for tasks like content moderation, sentiment analysis and extracting text/metadata from images.
Facebook广告API 101
1) The document provides an overview of the Facebook advertising API and how to get started using it. It discusses the different access levels for the API, how to authorize and get an access token, and examples of creating advertising campaigns, ad sets, ads and targeting audiences using the API.
2) It also covers important concepts like bidding and object specs needed to define ads, and recommends ways to familiarize yourself with targeting specs and estimating reach through the API.
3) The document aims to help developers understand how to leverage the Facebook advertising API to programmatically create and manage ad campaigns at scale.
Kaz Sato, Evangelist, Google at MLconf ATL 2016
Machine Intelligence at Google Scale: Tensor Flow and Cloud Machine Learning: The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn’t scale for production service, so you need a Distributed Training on the cloud eventually. Google has been building infrastructure for training the large scale neural network on the cloud for years, and now started to share the technology with external developers. In this session, we will introduce new pre-trained ML services such as Cloud Vision API and Speech API that works without any training. Also, we will look how TensorFlow and Cloud Machine Learning will accelerate custom model training for 10x – 40x with Google’s distributed training infrastructure.
TensorFlow 深度學習快速上手班--電腦視覺應用
This document discusses computer vision applications using TensorFlow for deep learning. It introduces computer vision and convolutional neural networks. It then demonstrates how to build and train a CNN for MNIST handwritten digit recognition using TensorFlow. Finally, it shows how to load and run the pre-trained Google Inception model for image classification.
深層学習（ディープラーニング）入門勉強会資料（浅川）
２０１６年１１月６日深層学習（ディープラーニング）入門勉強会資料（浅川）Pythonキャリアカレッジ
http://www.vantan-game.com/python/
TensorFlow 深度學習快速上手班--自然語言處理應用
This document discusses natural language processing applications using TensorFlow. It introduces natural language processing and the Word2vec neural network model. It then demonstrates an implementation of semantic operations using Word2vec embeddings trained on sample text data. Key steps include preprocessing the text, defining the computational graph in TensorFlow to train the Word2vec model, and obtaining the final word embeddings.
Vpon - 廣告效果導向為基礎的行動廣告系統
This document discusses Vpon's mobile advertising system and recommender model. It describes the basic concept, challenges, and infrastructure of Vpon's ad serving platform. It then focuses on the recommender system, outlining the design, implementation, and evaluation process. Key steps include calculating ad and user similarities, predicting user preferences, optimizing ad delivery, and continuously improving based on results. The recommender significantly increased click-through and conversion rates while reducing costs.
TensorFlow 深度學習快速上手班--機器學習
This document provides an introduction and overview of machine learning and TensorFlow. It discusses the different types of machine learning including supervised learning, unsupervised learning, and reinforcement learning. It then explains concepts like logistic regression, softmax, and cross entropy that are used in neural networks. It covers how to evaluate models using metrics like accuracy, precision, and recall. Finally, it introduces TensorFlow as an open source machine learning framework and discusses computational graphs, automatic differentiation, and running models on CPU or GPU.
Viewers also liked (20)
Machine learning with Google machine learning APIs - Puppy or Muffin?
Machine learning with Google machine learning APIs - Puppy or Muffin?
Google Cloud Platform Empowers TensorFlow and Machine Learning
Google Cloud Platform Empowers TensorFlow and Machine Learning
Google Machine Learning APIs - puppies or muffins?
Google Machine Learning APIs - puppies or muffins?
Machine Learning for Any Size of Data, Any Type of Data
Machine Learning for Any Size of Data, Any Type of Data
More from Amalan Dhananjayan
Why unity for mobile game development
Unity is a game development platform that overcomes the challenges of previous engines like HAXE, Cocos 2D-X, and LibGDX. It supports development for multiple platforms, has integrated ads and analytics to enhance games, and was designed specifically for game development with an easy-to-use interface. The document discusses Unity's advantages for mobile gaming like performance, efficiency, and compact games, as well as how it improved on earlier open source engines that had issues like difficult prototyping and limited support.
Small Teams (Pod Concept)
The document recommends breaking large teams into smaller pods or subgroups to better manage deadlines and risks, as having many large teams on tight deadlines increases management challenges. It notes that if two large pizzas are not enough to feed a team, the team is too big and should be broken into smaller pods.
Google Glass For Dummies
This slides are designed to explain what is a Google Glass for School children. Without going much into technology.
Google Glass in a Programmer's View
Google Glass is the next generation wearable smart device. This presentation explains some important aspects to be see understood before diving into program for Google Glass. What is the technologies used in it, how to approach as a developer are discussed. When comes to Google GLASS development there are 2 major approaches. 1 st is Native Glass app development and the other one is Glassware development. Take an overall idea about the glassware with the help of the architecture diagram of how it works.
Google Glass What Is it
What is Google Glass, a descriptive article on Google Glass for general public. Article does not have any development part.
Mobility Trends
Latest Mobile App development trends. Explains about the past current and the future trends and how it will affect the current Software development process. A future moving towards the mobile based software solutions.
More from Amalan Dhananjayan (7)
Recently uploaded
Public CyberSecurity Awareness Presentation 2024.pptx
Cyber security awareness slides for a busisness by TreeTop Security
GNSS spoofing via SDR (Criptored Talks 2024)
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Trusted Execution Environment for Decentralized Process Mining
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Fueling AI with Great Data with Airbyte Webinar
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
SAP S/4 HANA sourcing and procurement to Public cloud
SAP S4 HANA to Public cloud data object differences
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
AWS Cloud Cost Optimization Presentation.pptx
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
Free A4 downloadable and printable Cyber Security, Social Engineering Safety and security Training Posters . Promote security awareness in the home or workplace. Lock them Out From training providers datahops.com
Astute Business Solutions | Oracle Cloud Partner |
Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.
Recently uploaded (20)
Public CyberSecurity Awareness Presentation 2024.pptx
Public CyberSecurity Awareness Presentation 2024.pptx
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Trusted Execution Environment for Decentralized Process Mining
Trusted Execution Environment for Decentralized Process Mining
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
SAP S/4 HANA sourcing and procurement to Public cloud
SAP S/4 HANA sourcing and procurement to Public cloud
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Astute Business Solutions | Oracle Cloud Partner |
Astute Business Solutions | Oracle Cloud Partner |
Google Vision Api
- 3. What is Cloud Vision API ?
- 4. What Can It Do?
- 6. Face Detection Detect multiple faces within an image, along with the associated key facial attributes like emotional state or wearing headwear. Facial Recognition is not supported.
- 10. Integrated REST API Access via REST API to request one or more annotation types per image. Images can be uploaded in the request or integrated with Google Cloud Storage.
- 11. Thank You If you have questions, send me an email at adh@exilesoft.com Selfie Mood Amalan Dhananjayan, Software Engineer, Exilesoft(Pvt) Ltd